Math, Data & Computing

I was introduced to math, data, and computing in my first year of this study and learned about how data can be handled in various ways to make it easier to compare with the other data. Knowledgable in and about Jupyter, which is used to compile the collected data, visualize and communicate it in the form of different graphical models  to prove a hypothesis to reach a conclusion. Creative electronics helped understand ways actuators, and sensors could be used to creatively gather data, for a meaningful experience and usage. The goal was to track the weather changes, to indicate to the user the appropriate conditions for outdoor painting. Data was analysed and plotted using excel since it wasn't a priority for data to be analysed using data anlytical software. However, other quantitative and qualitative data has been cleaned and visualized in the form of box plots, histograms,  gaussian mixtures and so on. In a following course, namely "Making sense with sensors", was insightful to play around with real-time data, visualizing it and understanding the outcomes encouraging a positive change. 

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Further, the knowledge from my calculus and physics courses were used for prototyping. Data regarding emotional expressions and its accuracy were visualized after qualitative surveys. Textual data analyzations bring about understanding skills since it takes a certain level to read visualizations. Furthermore, in the course creative mechanical engineering, we dealt with computing and math skills through physics, to calculate the force and torque. These specific calculations were used for the handles which were charged by a marble to create a chain of actions (ruth goldberg machine) in order to open a beer bottle.

 

Below are just a few snippets of deliverables that were applied and produced during different courses in my study: